Situation at Rivers in New Zealand due to E. Coli Contamination: Analytical Essay

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New Zealand rivers – not so clean after all

Background

Tourism plays a big part in New Zealand’s export being a crucial part of the New Zealand economy. It is important for New Zealand to maintain a “100% pure” image as the Tourism New Zealand advert suggests. This is because countries are likely to purchase NZ exports if they think that it is coming from a ‘100% pure’ country. However, this “100% pure” image that Tourism New Zealand tries to portray might not be correct. It is shocking to find out that “more than 60 percent of monitored rivers in New Zealand are unsafe for swimming”(Stacy Kirk, 2013) and according to Charlie Mitchell, it is not safe to drink from half of the rivers in New Zealand due to E. coli contamination.

E. coli is a type of bacteria that is found in the intestines of humans and animals. E. coli affects many rivers in New Zealand, it is important that E. Coli/100mL of water is monitored in our rivers. When E. coli/100mL exceeds 550/100mL, it is deemed unsafe for swimming and drinking according to lawa (Land Air Water Aotearoa). E. coli can make its way into rivers from runoff water, sewage outflow causing caused by waste disposal in toilets and sinks and feces deposited by grazing cows or sheep. “More than 100,000 of treated waste is poured into the dirty Manawatu river each day” (Stuff, 2008), this is possible due to the lack of Government policies surrounding freshwater management. Back in 2010, Kiran Chug from Stuff said that ‘pollutants and toxic waste are still pouring into rivers’ even though the Government released a public statement two years prior ‘aimed at improving freshwater management’.

E. coli can be measured in two ways, using a microscope to count the units known as CFU (colony forming units) or estimating the units known as MPN (most probable number). The rivers in New Zealand were measured by NIWA and local councils. Some rivers could have been measured using the MPN method or the CFU method. This presents limitation as the rivers in New Zealand might not have been measured with the same method. Unpredictable weather could pose as another limitation. According to Environment Minister Amy Adams, heavy rain and wind “can churn up sediment…releasing pathogens back into the water.”

The response variable in this investigation is the number of E. coli/100mL, the explanatory variable is the year (2003 & 2013), the population is the New Zealand rivers in 2003 and 2013.

Question

I wonder what the difference is between the average number of E. coli/100mL in 2003 and the average number of E. coli/100mL in 2013, from New Zealand rivers in 2003 and 2013

Hypothesis

From the research that I have gathered, I hypothesize that there will be no difference in the average number of E. coli/100mL in New Zealand rivers from 2003 to 2013.

Purpose

The purpose of this investigation is to determine if there was a difference is between the average number of E. coli/100mL in 2003 and the average number of E. coli/100mL in 2013, from New Zealand rivers in 2003 and 2013, it would be important to conduct this investigation as it is important for New Zealand to maintain a ‘100% pure’ image. The results of this investigation could be used by the Government and the Ministry for the Environment as the results could indicate whether stricter freshwater policies need to be imposed.

Body:

Graph of sample distributions
Summary statistics
Year Min Q1 Median Mean Q3 Max Std. Dev. n
2003 1 39 200 637.26 490 7500 1254.9 86
2013 1 28 110 421.33 375.6 17000 1271 303
Features of sample distributions

Centre:

The two years above (2003 and 2013) shown on the box and whisker graph appears to be skewed to the right. In this case, since the mean value is significantly different from the median value, it appears that the mean has been affected by the shape. The median will give a more accurate representation of the average number of E. coli in 2003 and 2013. The 8 values past 3800 (3x Standard deviation) would affect the mean and therefore make the average less accurate. This is because the 8 values are extreme outliers

From the sample, the median number of E. coli/100mL in 2003 is 200/100mL whereas the median number of E. coli/00mL in 2013 was 110/100mL. The median number of E. coli in 2003 is 90/100mL more than the median number of E. coli in 2013. This means that in 2003, the rivers in New Zealand had more E. coli on average compared to the rivers in 2013 in the sample. I expected the median number of E. coli/100mL to be less than the median number of E. coli/100mL because of the cleaning initiatives. This makes sense because, in my research, I found out that the Manawatu council put aside $11 million in 2012 to “fix its water pollution issues” (Emma Horsely, 2012). There were also many initiatives like this between 2003 and 2013.

The middle 50% of E. coli/100mL in 2013 falls within the middle 50% of E. coli/100mL. This means that the difference between the medians might not be statistically significant as the boxes 2013 box overlaps with the 2003 box. This means that there may not be a difference between 2003 and 2013 back in the population.

Spread:

The number of E. coli/100mL varied a lot in 2003 and 2013. In 2003, the number of E. coli varied between 1 and 7500. Whereas the number of E. coli in 2013 varied between 1 and 17000. However, 2013 varied more than in 2003. There could have been many factors at play here such as floods in certain areas, river locations (urban, pastoral, and native areas), and rivers with sewage outflows.

Rivers that pass-through Wellington are considered as urban rivers and some rivers that pass-through Christchurch is considered as pastoral. According to Stats NZ “E.coli levels are 22 times higher in urban areas and 9.5 times higher in pastoral rivers compared with rivers in native forest areas”. This means that the number of E.coli could vary due to the river location.

Also, heavy rainfall in regions could also cause sewage overflow and an increase in runoff water which could increase E.coli/100mL.

In the sample, the middle 50% of the number of E. coli/100mL in 2003 was between 39 and 490, with an Inter-Quartile range of 451. On the other hand, the middle 50% of the number of E. coli/100mL in 2013 was between 28 and 375.6, an interquartile range of 347.6. This is surprising because I thought that the overlap between the 2 years would not be that big. This is because, over the years, the ministry of environment has tried to improve the river quality in New Zealand.

Shape:

The 2003 group is skewed to the right, the 2013 group also has the same skew. This means that both groups are asymmetrically distributed. There were a few rivers that exceeded 4000/100mL causing the upper 25% to have more variation than the lower 75% for both groups. However, the upper 25% of the 2013 group had more variation than the upper 25% of the 2003 group. This is because the Whareroa stream in 2013 had 17000 E. coli /100mL. it is also important to note that different methods could have been used to determine the number of E. coli/100mL such as the CFU and the MPN method. The rivers that were measured using the MPN method would have been estimates. This means that back in the population we might not have the same results. I noticed that both groups are unimodal and have modes that are close to 0, suggesting that majority of New Zealand rivers in both 2003 and 2013 were safe for swimming (during the time that the data was collected) as it did not exceed the 550/100mL mark. This is surprising as some articles wrote about 60% of New Zealand rivers not safe for swimming.

Unusual features:

There are 4 extremely large numbers of E. coli/100mL in each group exceeding 3800 E. coli/100mL (3 times the standard deviation). The highest recorded number of E. coli/100mL at 17,000 E. coli/100mL was from the Whareroa stream recorded in January 2013. This is an interesting figure as it was 31 times over the 550/100mL limit. Many factors could have played into the measurement of E. coli in this river. Upon research, the Whareroa stream is close to a farm and the data was collected on one of the hottest months in Wellington history (Jo Moir, 2013). There were also 7 other rivers that had an unusually large number of E. coli/100mL.

The Whareroa stream is located in Wellington and according to Tracks NZ, there is a farm close to the stream. The data was collected on one of the hottest months in Wellington history. This might have caused the livestock to drink from the stream

Graph of bootstrap distribution of the difference

State the Confidence Interval

In this investigation, the purpose was to find out if there was a difference between the average number of E. coli/100mL in 2003 and the average number of E. coli/100mL in 2013, from New Zealand rivers in 2003 and 2013. It would be more appropriate to use the median over the mean to measure the average number of E. coli/100mL as there were a few unusual values.

1,000 bootstrap resamples were taken from the sample and from these resamples, 95% of these confidence intervals will contain the actual difference between the median number of E. coli/100mL in 2003 and 2013 back in the population. The bootstrap interval helps us factor in sampling error

If I was to get another random sample of rivers in New Zealand, I would get different means, medians and etc. The difference of the medians that I got (90/100mL) is not enough to draw a conclusion that back in the population there is a difference between the medians in 2003 and 2013. This is why I need to consider sampling variation to determine whether the difference in medians in my sample was significant.

The confidence interval for the median difference between the 2 years (2003 and 2013) is from -10/100mL and 149.8/100mL. This means that the number of E. coli/100mL for both 2003 and 2013 is likely to be between -10/mL and 149.8/100mL.

Interpretation of the confidence interval of the difference

The width of the confidence interval indicates that the values are pretty much the same, meaning that there is a little variation in the sample. This is because both groups have big samples sizes

From the confidence interval shown above, I cannot make a call that there will be a difference in E. coli/100mL in 2003 and E. coli/100mL in 2013 as there is not enough evidence provided. This is because the confidence interval includes 0. This means that back in the population, the median E. coli/100mL in 2013 could be bigger, smaller, or the same as the median E. coli/100mL in 2003. I cannot make a call because it is probable that the difference between the median of the number of E. coli/100mL in 2003 and 2013 is 0.

Conclusion

The purpose of this investigation was to determine if there was a difference is between the average number of E. coli/100mL in 2003 and the average number of E. coli/100mL in 2013. In my research, I found out that New Zealand wasn’t as clean as the “100% pure” campaign claimed to be. I also found out that a lot of harmful things are pumped into our rivers every day and during 2003-2013 not much was done by the government to impose strict freshwater management. I predicted that there wouldn’t be a difference between the median number of E. coli/100mL in 2003 and 2013 due to the lack of Government intervention.

The results from the bootstrap graph show that there is not enough evidence to conclude there was a difference between the medians of the average number of E. coli/100mL in both groups. This is because the confidence interval contains 0. If I was to get another random sample, I would have different summary statistics, but I might be able to determine if there was a difference is between the average number of E. coli/100mL in 2003 and the average number of E. coli/100mL in 2013.

To expand this research, it would be interesting to investigate the average number of E. coli/100mL in other countries and if there has been an improvement from 2003 to 2013. The New Zealand Government has not been placing enough importance on its rivers and failure to recognize that many rivers are polluted will cause more of a problem in the future. Perhaps, other countries might also have an issue with lack of Government intervention concerning river cleanliness.

Bibliography

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